Highlighting Media Through Weighting of People or Contexts

ABSTRACT

Techniques and apparatuses for highlighting media through weighting of people or contexts are described. This document describes techniques that allow a user to quickly and easily highlight media, such as through generating a highlight reel. The techniques also enable selection of context and person weightings by which to tailor highlight reels.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of and claims priority to U.S.Utility patent application Ser. No. 14/231,644, filed Mar. 31, 2014,which in turn claims priority to U.S. Provisional Application Ser. No.61/878,864, filed Sep. 17, 2013, the entire disclosures of which arehereby incorporated by reference in their entireties.

BACKGROUND

background description is provided for the purpose of generallypresenting the context of the disclosure. Unless otherwise indicatedherein, material described in this section is neither expressly norimpliedly admitted to be prior art to the present disclosure or theappended claims.

Current techniques for creating photo slideshows enable users to selectphotographs, an order for those photographs, transition effects betweeneach selected photograph, accompanying music, and an amount of time thateach photograph is presented. These current techniques allow goodflexibility for users through selecting which photos, where in theslideshow, time presented, music played, and so forth. Creating photoslideshows using these current techniques, however, rely on substantialinput from the user. The user, to have a photo slideshow that isdesirable to watch, often has to pour over dozens or even hundreds ofphotos, decide which ones to include, what order to present them, whattransitions to present between each, time shown for each, and so forth.This can be time consuming and cumbersome for users even for fairlysimple photo slideshows.

Using these current techniques can be even more time consuming anddifficult if the user wishes to create a moderately complex photoslideshow. Assume, for example, that a mother of a kindergartener wishesto create a photo slideshow to present at the kindergarten classes'year-end party. If she wants to balance how many times each child in thekindergarten is shown—so that the photo slideshow is fair to thechildren—she may have to pour over hundreds of photos for that year,make sure she has at least two or three images for each child, whilelikely also wanting to show each child at multiple events from the year,and so forth. Even for these simple criteria—number of times shown andshowing each child at more than one event—can take substantial time andeffort using current techniques.

BRIEF DESCRIPTION OF THE DRAWINGS

Techniques and apparatuses for highlighting media through weighting ofpeople or contexts are described with reference to the followingdrawings. The same numbers are used throughout the drawings to referencelike features and components:

FIG. 1 illustrates an example environment in which techniques forhighlighting media through weighting of people or contexts as well asother techniques described herein can be implemented.

FIG. 2 illustrates a detailed example of a computing device shown inFIG. 1.

FIG. 3 illustrates example methods for grading video clips.

FIG. 4 illustrates example methods for grading images.

FIG. 5 illustrates example methods for creating and sharing highlightreels, in some cases including weighting of contexts in source media.

FIG. 6 illustrates an example interface enabling selection of sourcemedia through media albums.

FIG. 7 illustrates an example interface presenting and enablingalteration of context weightings determined from source media.

FIG. 8 illustrates an example reel preview interface.

FIG. 9 illustrates example interfaces enabling selection of advancedoptions, music, and to remove or rearrange a reel preview's images andsubclips.

FIG. 10 illustrates an interface presenting and enabling alteration ofweightings of persons and contexts through use of slider bars.

FIG. 11 illustrates an example interface that enables quick and easyselection of persons with which to share a highlight reel.

FIG. 12 illustrates example methods for creating a highlight reel basedon quality metric values and persons shown in the media.

FIG. 13 illustrates example methods that enable weighting both personsand context as part of highlighting media.

FIG. 14 illustrates an example interface enabling selection to weightpersons through slider bars or gestures, the persons represented withthumbnail images.

FIG. 15 illustrates an example interface that presents an image for eachperson in a highlight reel or reel preview where the image sizecorresponds to the person's weighting in the highlight reel or reelpreview.

FIG. 16 illustrates the example interface of FIG. 15 but after selectionto alter weightings of persons.

FIG. 17 illustrates various components of an example apparatus that canimplement techniques for highlighting media through weighting of peopleor contexts.

DETAILED DESCRIPTION Overview

This document describes techniques that allow a user to quickly andeasily generate a highlight reel. The techniques may do so in variousmanners, including through quick and easy selection and weighting ofpersons and contexts used to create a highlight reel. The techniques mayalso or instead create highlight reels based on when and where peopleappear in scenes within media, quality metrics, and contextual varietyof media from which the highlight reel is sourced. The techniques alsoenable sharing of these highlight reels, in some cases automatically oncreating the highlight reel, such as to persons known to be in thehighlight reel.

The following discussion first describes an operating environment,followed by techniques that may be employed in this environment alongwith example user interfaces, and concludes with an example device.

FIG. 1 illustrates an example environment 100 in which techniques forhighlighting media through weighting of people or contexts and othertechniques related to highlight reels can be implemented.

Environment 100 includes a computing device 102, a remote device 104,and a communications network 106. The techniques can be performed andthe apparatuses embodied on one or a combination of the illustrateddevices, such as on multiple computing devices, whether remote or local.Thus, a user's smart phone may capture (e.g., take photos or video) someof the media from which the highlight reel is generated, as well asreceive other media from other devices, such as media previouslyuploaded by a friend from his or her laptop to remote device 104,directly from another friend's camera through near-field communication,on physical media (e.g., a DVD or Blu-ray™ disk), and so forth. Whetherfrom many or only one source, the techniques are capable of creating ahighlight reel at any of these devices.

In more detail, remote device 104 of FIG. 1 includes or has access toone or more remote processors 108 and remote computer-readable storagemedia (“CRM”) 110. Remote CRM 110 includes reel generator 112 andaudiovisual media 114. Reel generator 112 generates a highlight reel 116based on one or more quality metrics 118 and using source media 120.More specifically, reel generator 112 receives a selection, or someinformation by which to make a selection, of source media 120 fromaudiovisual media 114. With this source media 120, reel generator 112generates highlight reel 116, which may be generated based onuser-selected or unselected quality metrics.

Quality metrics 118 include many different measures of an image or imageportion's quality, as well as audio and video quality, such as singleframes in video or video subclips. Some quality metrics are independentmetrics, and thus values given for an image being analyzed are not basedon values given for other images, such as image brightness and eyeblinks. Other quality metrics are relative metrics based at least inpart on a quality metric value given to another image, such asuniqueness. Example quality metrics 118 include, for example:brightness, color variance, overall sharpness, accumulated-faces area,head orientation, face or faces smiling, eye blinks, locations of one ormore faces within the image or frame, eye focal point, aspect ratio ofthe image or frame, uniqueness, mistakes, and face blur.

Reel generator 112 also includes or has access to an interface 122.Interface 122 enables quick and easy selection of various people,contexts, events, and so forth as described below. In some cases,interface 122 enables simple and intuitive selection to weight persons,contexts, and events such that a user is able to tailor or adjust ahighlight reel to his or her preferences.

Reel generator 112 further includes or has access to associations 124and relatedness 126. Both associations 124 and relatedness 126 can beused by reel generator 112 to determine which images and subclips to useto create a highlight reel.

Associations 124 includes one or more of contexts 128, events 130, andpersons 132. Images and video clips include scenes that have one or morecontexts 128. Contexts 128 include scenes, such as indoor, outdoor, ofparticular seasons (autumn, summer), nighttime, daytime, work, and home,though they may also be more specific, e.g., in a mall, at dinner, of apicnic, on a boat or plane, identified with particular items (fishingpole, soccer ball, baseball bat, Frisbee, people wearing shorts, skirt,helmet, or tie), and so forth. Contexts 128 can also be based on when orwhere media was captured, such as at breakfast time, naptime, weekends,sports field (e.g., kids soccer field or professional rugby stadium),while the capture device was moving rapidly (e.g., in a car), and soforth. Context 128 also includes association with particular events,such as images and video clips taken at a concert (based on location ora person's capture device where the person's calendar indicates theywill be at the concert) or saved in an album selected to organize media,such as media taken during a particular vacation. Events 130, which areconsidered a type of context 128 in some cases, are events associatedwith the image or clip, such as a time, location, or theme at whichmedia is captured. Events 130 may include calendar events or based onlocation (e.g., the soccer field or concert above).

Assume for example that two friends meet at a park for a picnic. Thepicnic can be an event associated with media captured during the picnicwhile the park can have numerous contexts for the media, such asoutdoors, sunny, windy, people eating, and so forth. Associations alsoinclude persons 132, which include people in the media or associated insome way with the media, such as a person that is in the media or that,while not recognized or tagged for an image, is at a shared calendarevent at which the image was captured.

Relatedness 126 includes contextual variety 134 and time-distance 136.In creating a highlight reel, reel generator 112 may select images andsubclips from source media 120 based on values given for contextualvariety 134 and time-distance 136. Assume, for example, that varioushigh-quality images (measured by quality metric values) indicate thatsix video subclips are of high quality. Assume further that reelgenerator 112 is deciding on which four to include (e.g., to keep thehighlight reel from being too long). One measure of what to keep is tovalue variety—thus if five of the subclips are outdoors (and thus havelow contextual variety with each other), they are of lower value thanthe high-variety single indoor subclip. Also, subclips further away fromeach other in time taken are of higher value. If three of the subclipsare taken within 10 minutes of each other and the other three are takendays apart, the three taken within 10 minutes are given a lower valuefor use in a highlight reel as being too related to each other.

As noted in part above, the techniques may generate highlight reel 116automatically and with little or no explicit selection of what images orwhich persons to include. The techniques may, however, enable selectionof quality metrics and weights of persons and contexts. Thus, a user mayselect to highlight Bella and Ann, at which time reel generator 112determines source media 120 of audiovisual media 114 that has Bella orAnn or includes content associated with either or both of them, e.g.,photos and video captured at a concert that both Bella and Ann attended.Time-consuming and explicit selection of particular images and so forth,however, can be avoided by the user. In cases where the user wants morecontrol, the techniques enable selections but in a quick and easy-to-usemanner.

Audiovisual media 114 includes available media from which to source ahighlight reel. Audiovisual media 114 may include photos, videos (whichmay include audio), and music, or portions thereof. As will be describedbelow, a subset of available media can be selected as source media 120for a highlight reel, though this source media 120 can be drawn orreceived from many sources as noted above. Source media 120 includesimages 138 and video clips 140 though both are not required for creationof highlight reel 116. Note that source media 120 can include apreviously created highlight reel, which in some cases can aid increating a new highlight reel more quickly or with fewer computingresources. Media in a previously created highlight reel may includemedia not separately within source media 120. Multiple users may sharetheir highlight reels of a same event for creation of an overarchinghighlight reel based on the prior highlight reels, for example.

Images 138 can be captured images, e.g., photographs, or portionsthereof, such as 60 percent of an image cropped to fit a desired aspectratio or remove undesirable elements, such as a finger obscuring part ofan otherwise high-quality image. Video clips 140 are videos, which aregenerally captured and include audio, though this is not required.Subclips and images from single frames can be selected from video clips140, which is described in detail below.

With regard to the example computing device 102 of FIG. 1, consider adetailed illustration in FIG. 2. Computing device 102 can each be one ora combination of various devices, here illustrated with eight examples:a laptop computer 102-1, a tablet computer 102-2, a smartphone 102-3, avideo camera 102-4, a camera 102-5, a computing watch 102-6, a computingring 102-7, and computing spectacles 102-8, though other computingdevices and systems, such as televisions, desktop computers, netbooks,and cellular phones, may also be used. As will be noted in greaterdetail below, in some embodiments the techniques operate through remotedevice 104. In such cases, computing device 102 may forgo performingsome of the computing operations relating to the techniques, and thusneed not be capable of advanced computing operations.

Computing device 102 includes or is able to communicate with a display202 (eight are shown in FIG. 2), an image-capture device 204, one ormore processors 206, and computer-readable storage media 208 (CRM 208).CRM 208 includes reel generator 112, audiovisual media 114, highlightreel 116 (after generation, unless included in source media 120),quality metrics 118, source media 120, and interface 122. Thus, thetechniques can be performed on computing device 102 with or without aidfrom remote device 104.

These and other capabilities, as well as ways in which entities of FIGS.1 and 2 act and interact, are set forth in greater detail below. Theseentities may be further divided, combined, and so on. The environment100 of FIG. 1 and the detailed illustration of FIG. 2 illustrate some ofmany possible environments capable of employing the describedtechniques.

Example Methods for Grading Images and Video Clips

To help enable fast creation of high-quality highlight reels, as well assave high-demand computing and power resources, the techniques may gradeimages and video clips prior to receiving a selection to build ahighlight reel. This grading can include those set forth above, such asdetermining image quality, as well as determining associated events,contexts, and people. Grading of images and video clips can be performedat downtimes, immediately responsive to the media being captured, orwhen a capturing device is not on battery power. Whenever performed,grading of media prior to selection to create a highlight reel canenable faster creation or higher-quality highlight reels.

FIG. 3 illustrates example methods 300 for grading video clips. Theorder in which these and all other methods described here are presentedis not intended to be construed as a limitation, and any number orcombination of the described methods' operations can be combined invarious orders to implement a method, or an alternate method, as well asin combination with, in whole or in part, other methods describedherein.

At 302, video clips are received. As noted in part above, this exampleof source media can be received from one or multiple sources. Thus, thevideos used can be captured by a device that performs the method or fromanother device and received at the device that performs the method(e.g., captured by camera 102-5 and received by remote device 104).Videos may instead be captured by numerous devices, such as by variouspersons at an event and shared for one or a collection of the devices togenerate a highlight reel.

At 304, quality metric values for video clips are determined by gradingthe video clips and subclips of the video clips. As noted in part above,these quality metric values are determined based on various differentquality metrics 118. In some cases the quality metric values aredetermined based on a frame-by-frame analysis, though this is notrequired. Quality metric values can be calculated based on an averageper-frame quality for frames in each of the video clips. Other mannerscan instead be used, however, such as motion and facial tracking todetermine relevant subclips with which to further analyze for quality.

In more detail, reel generator 112 can determine values for the variousquality metrics as floating points, and these values can be associatedwith a positive or negative for inclusion in a highlight reel. Consider,for example, the following metrics, values given, and use of thesevalues.

Image brightness can be calculated as an average value of a Y channelover all pixels of a downscaled frame. The resulting value is normalizedto [0; 1], with brighter images (frames or a portion thereof) optionallybeing considered better.

Image color variance can be calculated by determining the standarddeviation of each of the R (red), G (green), and B (blue) channels, andaveraging these values. The resulting value is normalized to [0; 1],with bigger color variance optionally considered better.

Overall image sharpness can be determined in various image-analysismanners known and given a value in the [0; 1] range, though it may benormalized, with higher sharpness considered better.

Accumulated faces area can be calculated by determining a number offaces and dividing that number by the image area of the faces. Theresulting value is normalized to [0; 1] with more faces consideredbetter and larger faces considered better (in some cases, thoughface-size variance can also be desired); several large faces may beconsidered better than many small faces, depending on the user'sselection and/or display size on which the highlight reel is intended tobe presented (e.g., large screen display or smart phone display).

Head orientation can be determined to be either a frontal face or aprofile face. Centered faces are optionally considered to be better. Afrontal face is centered if it is lying in the middle third on thehorizontal axis and a profile face is considered to be centered if it islying in the left or right thirds and is facing toward the center of theframe.

Faces smiling can be determined based on whether or not faces aresmiling, with the rates being normalized to [0; 1] with smiling facesoptionally considered better. Eye blinks can be determined based onwhether or not faces in an image are blinking, and the rates arenormalized to [0; 1] with blinks on faces considered worse.

Location of a face or faces in the image can be determined based onfacial recognition providing a center, box, or eye location, andmeasuring that location relative to borders of the image. Values can beused to measure this, such as with a face at a bottom corner having arelative low value in the [0; 1] range. Location issues can, in somecases, be addressed by cropping and expanding the image, though this mayreduce resolution and context.

Aspect ratio can be measured and given a value, again with values in the[0; 1] range. Some aspect ratios are less desired, especially in caseswhere a highlight reel is desired to be shown with a particular aspectratio that does not match the aspect ratio of the image. Thus, for ahighlight reel selected for 16:9, an image having an aspect ratio of 4:3may be less desirable. For many mobile devices, the aspect ratioselected for the highlight reel may be 9:16 or some othertaller-than-it-is-wide aspect. The techniques may also take this intoaccount.

Uniqueness can be determined based on similarity with other images beingused to build the highlight reel, with values in the [0; 1] range. Thus,an image having the same three people smiling directly into a camera(even if they are dressed differently, etc.) may be given a lesservalue. The techniques, by so doing, can provide a highlight reel withvariety and that emphasizes differences. A lack of uniqueness, however,can be addressed in some cases by reducing a display time for and/orbunching together these similar images. Thus, for three images havingthe same two people both looking directly at the camera and smiling, thetechniques may choose to show all three in rapid succession.

Mistakes, such as images not intended to be taken, or with a finger orsome other obstruction, can be determined and given a value in the [0;1] range. In some cases an image taken by mistake is determined throughother manners, such as blurriness, lack of faces, and so forth as well.Images that are nearly all black or white or with little contrast, forexample, can be given lesser values or excluded completely.

Face blur can be determined based on the blurriness of faces in animage, with values in the [0; 1] range. Images with blurry faces areoptionally considered worse, though in some cases movement of faces invideo can be considered desirable, which may be indicated by multipleblurry images over multiple frames.

At 306, relatedness values are determined between the various videoclips. As noted above, relatedness 126 includes contextual variety 134and time-distance 136. These are but two ways in which to measure howclosely related clips and subclips are to each other. Relatedness can beused in determining a highlight reel by valuing variety (or lackthereof).

By way of example, consider two subclips of a video clip that are closetogether within a media timeline of that video clip (e.g., inchronological proximity). These subclips are generally considered lessvaluable than subclips that are more distant in the timeline. Thus,time-distance 136 measures this value based on their relatedness.Another example of relatedness is subclips from a same album when sourcemedia 120 includes multiple albums. As variety is generally consideredmore valuable than homogeneity, a time distance penalty can be assessedfor subclips from the same album. This is not the case, however, whensource media 120 is from only one album or event.

At 308, the quality metric values and the relatedness values for thevideo clips are stored. These values are effective to enable reelgenerator 112 to determine a subset of the video clips or subclips ofthe video clips that highlight the video clips (e.g., with a highlightreel).

At 310, a subset highlighting the video clips is determined based uponthe stored values. In this particular example, reel generator 112determined subclips for use in highlight reel 116 based on qualitymetric values and relatedness values for various video clips. This isnot intended to be limiting to just video clips, however, as images mayalso be used as source media 120. Generating highlight reels is setforth in substantial detail below and so is not detailed here.

Optionally, at 312, the techniques may wait to proceed to operations 304and 306 until a computing device on which methods 300 are beingperformed is determined to be on non-battery power or in a state oflow-resource usage at 312. Thus, when resources, such as processingresources, are in demand reel generator 112 may forgo using theseprocessing resources. As methods 300 require power, reel generator 112may wait until the computing device is no longer on battery power.

In addition to determining quality metric values and relatedness valuesas part of methods 300, the techniques may also recognize persons in thevideo clips and store identifiers for recognized persons effective toenable later creation of a highlight reel with little or no facialrecognition required at that later time.

Note that reel generator 112 may determine that, based on quality metricvalues and in some cases relatedness values, some video clips forportions of the clips should be excluded from consideration for use in ahighlight reel. Similarly, reel generator 112 may determine that certainportions of the video clip should be candidates for use in the highlightreel, such as a small subclip, which is a portion of the video clip. Byway of example, consider a video clip taken of an entire inning of aLittle League baseball game. Assume that this video clip is 14 minuteslong and includes substantial portions in which very little movement isrecorded, portions that are obscured by a hand or arm, and are washedout by the capture device being pointed toward the sun. Reel generator112, performing methods 300, may remove from consideration theseportions of the video clip.

FIG. 4 illustrates example methods 400 for grading images. At 402, animage is received. This image can be one of the many described herein,such as images 138 of audiovisual media 114.

Methods 400 may proceed directly to operation 404 or 406. Reel generator112, for example, may wait to perform future operations or proceed. At404, if a computing device performing operations of methods 400 is onnon-battery power or low resource usage, methods 400 proceed tooperation 406 if not, methods 400 may wait.

At 406, images are graded based on quality metrics to provide qualitymetric values. As noted above, these quality metric values can befloating-point values for each image, though this is not required.

Optionally, methods 400 may proceed to operation 408 prior to operation410. At 408, association of a received image is determined for variouspersons, contexts, or events. This can be as simple as performing facialrecognition on an image to determine a person in the image. Otherexamples include determining that an image has a particular context orwas taken during a particular event.

At 410, quality metric values and/or associations are stored. Similarlyto methods 300, this enables reel generator 112 to more quickly or withhigher quality generate a highlight reel responsive to selection to doso. Operations of methods 400 may be repeated effective to continue tograde images, shown at a dashed repeat line in FIG. 4.

At 412, a subset that highlights the image and other images isdetermined based on these values. This subset can be a portion used tocreate a highlight reel or represent the highlight reel described below.

In some cases battery power and resource usage is less important becausemethods 300 and 400 are performed at least in part by remote device 104.In such a case, images are received from one or more computing devices102 over communication network 106 and by remote device 104. In such acase, transmission bandwidth and transmission resources can instead befactors, but these factors affect the methods prior to receiving thevideo clips or images. Thus, the techniques may wait to transmit imagesand videos until these resources are available or the power cost totransmit is not drawn from a battery.

Example Methods for Creating Highlight Reels

With or without prior grading of media as noted in methods 300 and 400above, the techniques are capable of creating highlight reels thathighlight source media. This highlighting can be based on context,quality, and persons. This highlighting can be performed with little orno input from users. In cases where a user desires more control, thetechniques enable quick and easy selection of source media, persons, andcontext.

FIG. 5 illustrates example methods 500 for creating a highlight reelbased on quality metrics and contextual variety or selected contextualweightings.

At 502, source media is received. Receiving source media may includeretrieving selected source media from remote sources or local memory. Insome cases source media is selected to narrowly focus the createdhighlight reel. Also, source media can be selected in various manners,some of which are illustrated in FIG. 6. This source media can beselected prior to creation of the source media, in whole or in part. Auser may select, for example, future media to be the source for thehighlight reel. Examples include selection of an event that is currentlyoccurring or is scheduled to occur later and thus images and videocaptured during that event to be used as the source media for thehighlight reel. Source media may then be received automatically oncompletion of the event.

By way of example consider FIG. 6, which illustrates selection of sourcemedia through media albums. In this example, six media albums areillustrated in an album selection interface 602. Three of these mediaalbums are further illustrated in their own user interfaces responsiveto selection of a graphical album identifier within album selectioninterface 602. Of these three media albums, two are directed to eventsand one is directed to a particular person. In the first media album,illustrated at vacation album 604, media captured during a vacationbicycle touring the Curia) wine region of Chile, South America isorganized into the album. In the second media album, illustrated atconcert album 606, media captured during a concert is organized into thealbum. In the third media album, illustrated at person album 608, imagesand video clips that show Bella are organized. Thus, reel generator 112may receive selection of source media through selection of an album ormultiple albums.

By way of another example, consider a case where four friends have acalendar event where they are all going to the same party. They canselect, or by default be selected, to agree to share media from thatparty. Assume that each of the friends take pictures, videos, and soforth. The techniques can determine when the event begins, such as bythe scheduled time or by when each arrives (e.g., by physicalproximity), and when the event ends (e.g., by calendar event ending) orby dispersing from the party (e.g., no longer in physical proximity).Source media is then determined to be media captured by devicesassociated with these four friends during the event, which is thenshared sufficient for reel generator 112 to have access to the sourcemedia. On the event ending, each of the devices can, either due to aprompt received from a device generating the highlight reel, or on theirown share the media.

At 504, contextual variety and/or multiple contexts for images and videoclips within the source media are determined. Determining contextualvariety can be based on previously determined contexts, or contexts canbe determined as part of operation 504. In some cases as noted above,contextual similarity can be penalized so that greater contextualvariety is shown in the highlight reel. In some cases, however,contextual variety is less desired, such as in cases where a particularalbum is selected for highlighting, or on selection of contexts desiredby a user.

Note that further refinements on media to be used as source media, orcriteria by which images are used in the highlight reel, may includesource media that includes some number of the members of the group(e.g., two or more of the four friends). Ways in which the highlightreel is shared can be based on this selection, which is described indetail below.

This selection of source media can also or instead indicate the personsmaking the selection, such as the four friends going to the party. Insuch a case, reel generator 112 can determine that the media capturedduring the event by these devices includes images having these friends,which can aid or replace a need for facial recognition in some cases.The techniques may then forgo requiring selection (e.g., tagging) ofimage portions for faces that are not recognizable by facial recognitiontechniques. Instead, the techniques may simply assume that the imagesinclude the persons or are relevant to those persons that captured themedia, and share a highlight reel using this source media on that basis.

At 506, reel generator 112, through interface 122, presents a graphicaluser interface enabling selection to weight contexts. The contexts canbe presented at their expected weighting based on the contextsdetermined in source media 120 (e.g., the source media for the fourfriends from the party), or instead weightings can be presented evenlyfor selection.

By way of example, consider FIG. 7, which illustrates graphicalcontext-weighting interface 702. Interface 702 presents contexts atweightings determined from source media 120. In this case currentweightings have a relatively high weighting of indoor scenes, imageswith many persons in them, few albums/sources (here one album but foursources—from each of the four friends), and mixed facial orientationsrather than predominantly portrait (face-forward) images.

At 508, selection to weight one or more of the contexts is received.These weightings can be altered quickly and easily by a user, such as toweight more to facial orientations having portraits or that includefewer persons shown in each image. Note that contextual weighting can beperformed before source media is even selected, and thus be a criteriaon which source media is determined. Contextual weightings can also beperformed after source media is determined but before creation of a reelpreview. Further still, weightings can be altered after presentation ofa reel preview. Thus, selection to alter a weighting can alter a finalhighlight reel by altering source media or which subset of media is usedto highlight the source media.

At 510, a subset of the images and video clips by which to highlight thesource media is determined. This determination can be based on thecontextual variety of the images in the video clips and quality metricvalues of the images and video clips. As noted above, it may further bebased on selected weightings of contexts or persons.

At 512, the subset of the images and video clips are arranged into areel preview. Reel generator 112 may present this reel preview andenable selection to alter or approve the reel preview. An exampleinterface through which a reel preview can be viewed is shown in FIG. 8,at reel preview interface 802. The reel preview can be approved throughfinal selection interface 804. Operation 512 may arrange images into areel preview a similar manner to generating a final highlight reel. Toreduce processing time and resources, however, reel generator 112 maypresent the preview without encoding the preview, and using sequentialsubclips of one or more of the video clips. These sequential subclipsare presented by playing start and stop points within the respective oneor more video clips rather than separate out or separately store thesubclips.

At 514, a selection to alter or prove the reel preview is received.Returning to FIG. 8, through reel preview interface 802, a user maywatch the preview and select to alter or approve the reel preview. Ifaltered, methods 500 proceed along alteration path to perform one ormore operations of methods 500 again. If approval is received, methods500 proceed along approval path to operation 516.

The techniques enable various different manners in which to quickly andeasily alter or customize the highlight reel responsive to reviewing thereel preview. In one such case, the user may select a guide view 806,through which to remove, shorten, or rearrange images and some clips inthe highlight reel. The user may, for example, drag-and-drop images andsubclips to rearrange the highlight reel through guide view 806. Otheruser interfaces are also shown, through which reel generator 112 enablesusers to alter a reel preview. For example, consider FIG. 9, whichillustrates examples of operation 514 of FIG. 5, including advancedoptions interface 902, music selection interface 904, and removal andrearrange interface 906.

Advanced options interface 902 enables a user to select a title andlength, as well as select additional interfaces through to select visualtransitions and effects (not shown), edit photos or video, and selectaccompanying music. Music selection interface 904 enable selection ofvarious types of accompanying audio, in this case a song by Paul Simonis selected having a similar length to that of the reel preview. Removaland rearrange interface 906 provides controls through which to increaseor decrease a number of images (e.g., photos) or subclips, as well asremove images and subclips graphically.

Another advanced option is to alter weightings of persons, imageattributes, or contexts. Consider, for example, FIG. 10, whichillustrates person and context weighting interface 1002. Here fourcontexts and two persons' current weightings in the reel preview arepresented. The interface enables a user to select, quickly and easily,to increase or decrease contexts and person weightings (e.g., outdoorscenes or to focus on one of the two persons shown).

By way of example consider a situation where a user selects to makesignificant numbers of alterations to a reel preview, includingincreasing the playtime, removing a subclip, rearranging the images,selecting accompanying audio, and increasing a weight of scenes showingthe outdoors, and decreasing a weight of scenes to only one of thepersons shown. Even with all of these changes, the techniques permit theuser to do so quickly and easily. After these selections, methods 500return to previously performed operations to create another, altered,reel preview. Reel generator 112 then presents the altered reel preview,which here we assume is approved.

At 516, methods 500 generate the final highlight reel. In some casescreating the final highlight reel encodes the subset of the images andvideo clips included within the final highlight reel and createsmetadata for the final highlight reel. This metadata can be used tocreate a future highlight reel using this particular highlight reel assource media. On selection to finalize the highlight reel, and thusapprove the reel preview, final approval interface 804 can be presented.

Operation 516 can generate the final highlight reel automatically andwithout further selection. Further at 518, methods 500 may proceeddirectly to share the highlight reel with the persons shown in thehighlight reel or others determined to be interested in the highlightreel.

In some cases, operation 518 enables a user to select persons with whichto share through a user interface having visual identifiers for persons.Selection is enabled through these visual identifiers or in othermanners, such as a list of the person's names, pictures, a contact listhaving the same, and so forth.

Consider FIG. 11, which illustrates an example interface 1100 enablingquick and easy selection of persons with which to share a highlightreel. For this example, assume that Bella goes on a bike tour with herfriends Ryan and Mark through the wine country around Curico, Chile.Assume also that Bella takes photos and videos and selects, eitherbefore or after the tour, to create a highlight reel for her wine tour(e.g., by selecting an album of media covering this event). With thehighlight reel complete, Bella wishes to share the highlight reel withher friends, Ryan and Mark.

The techniques can present these three people based on various criteria,such as showing photos from the highlight reel that show a largestnumber of images in which people are shown, either a largest total or alargest number of images in which faces are recognized. The techniquesmay also or instead show multiple photos (including still portions of avideo) that the techniques determine include faces for persons,including allowing a user to quickly and easily move through the variousphotos to find those having the desired persons. In this example a photo1102 (shown in line drawing) is presented that identifies three persons(Bella, Ryan, and Mark), their faces shown in blocks with accompanyingnames for each.

Interface 1100 enable immediate selection for all identified personswith a single gesture, such as a gesture circling all three faces or atap on share-to-all control 1104. On selection reel generator 112 sharesBella's highlight reel with Ryan and Mark (and Bella, in some cases) ina default or previously selected manner.

In some cases, however, additional selections are enabled. These mayinclude a determination that certain persons, which may or may not be inthe highlight reel, are likely to be interested in the highlight reel.Consider a case, for example, where a highlight reel is created having amom and one of her children. This created highlight reel can bedetermined to be of interest to the child's grandmother based on anexplicit selection or history of sharing images, video clips, orhighlight reels with the grandmother when the child is recognized.Similarly, by selection or determination, close friends mayautomatically be presented for selection (or de-selection) to be sharedthe highlight reel. For the ongoing example of Bella's highlight reel ofher Curico wine tour, reel generator 112 may enable selection of Bella'sbest friend, Bella Nguyen, even though Bella did not go on the winetour.

The sharing can be performed through various communication systems,including near-field-communication or personal-area-networkcommunication from device-to-device (Direct Share), social media sharing(Facebook™), email (Gmail™), texting to a phone (Text SMS), and onlineserver storage (Google Drive™)

Permission can be required to share the highlight reel. Permission canbe received through a personal area network (PAN) or near-fieldcommunications, as well as various communication networks. Furthermore,permission can be received through explicit selection, such as whenresponding to an electronic invitation (e.g., a calendar acceptance oran Internet-based invitation in which an RSVP or similar is indicated),or implicitly by default for those that accept the invitation. Generallysuch a default selection is noted through an indicator or text in thecalendar or Internet-based invitation. Other indications can beincluded, whether permission is explicitly indicated or by default, suchnoting such on photos and videos when taken or edited.

Concluding methods 500, reel generator 112 may determine media contextsand quality prior to a selection or determination to create a highlightreel. Operations 520 and 522 can be performed as part of methods 300 or400, for example. In some cases, however, media quality and contexts aredetermined during methods 500, after receiving source media or selectionto create a highlight reel.

FIG. 12 illustrates example methods 1200 for creating a highlight reelbased on quality metric values and persons shown in the media.

At 1202, media quality is determined for images and video clips. Thismay be performed as noted herein, such as methods 300 and 400. At 1204,persons to highlight in the highlight reel are determined. To determinewhich persons to highlight, reel generator 112 may perform facialrecognition on the selected source media and then present these personsfor additional selection by a user.

In some other cases, however, persons are selected prior to selection ofsource media. Selection can be received in various manners, such as textentry, contact list selection, social networking selection (e.g., to puton a person's social page or “wall”), group selection (e.g., the user'sfriends or persons associated with the highlight reel), a sharedcalendar event, and so forth. In such a case, reel generator 112 maypresent many persons known to the user from which the user may select tocreate a highlight reel. Determining persons to highlight, therefore,may be independent of the media currently available to reel generator112. After selection of these persons, reel generator 112 proceeds tooperation 1206.

At 1206, images are determined based on the persons and the qualitymetric values. As noted, this may be based on selected source media, oraudiovisual media available or accessible by reel generator 112 onselection of persons to highlight. Reel generator 112 may analyzeaudiovisual media 114 of FIG. 1, for example, to determine source media120 from audiovisual media 114 based on the persons recognized, such asthose previously tagged or through facial recognition.

By way of example, assume that a user selects to create a highlight reelof herself at operation 1204. Reel generator 112 may then determinewhich media of audiovisual media 114 includes her face, treat this assource media 120, and then determine which of this source media 120highlights her based on quality, total length of highlight reel,contextual variety, variety of other persons also in source media 120(to show her with her various friends), and so forth. For example, reelgenerator 112 may rank images and clips by variety and quality, and thenpull from the top of the ranked media in a greedy manner until aselected target duration is met. The duration can also be determinedwithout selection based on the quality and variety or based on how muchsource media 120 was drawn from, e.g., some percentage of source media.

At 1208, the determined images and video clips are arranged into a reelpreview. These determined images and video clips or subclips can bearranged for visual variety, e.g., contexts spread over the reelpreview, or grouped by event or context, e.g., showing highlights of aconcert and then of a vacation but not mixing the two. Further, thearrangement can spread subclips out from still images and so forth. Asnoted herein, these images and clips can be arranged and customized by auser quickly and easily if the user so desires. Examples of reelpreviews are shown in FIG. 8.

At 1210, alterations or approval are received. Example alterations andapprovals are described herein, including at operations 514 in methods500, and illustrated in FIGS. 8, 9, and 10. Methods 1200 proceed alongan alteration path to repeat one or more operations if an alteration isreceived. If the reel preview is approved, methods 1200 proceed along anapproval path to operation 1212.

At 1212, a final highlight reel is generated. This is also described indetail elsewhere herein. Methods 1200 may proceed to receive additionalimages or video clips at operation 1214 or to operation 1216. Thus, insome cases the techniques proceed to share the final highlight reel withthe persons of highlighted at 1216. Alternatively or in additionhowever, methods 1200 may automatically update the final highlight reel.At 1214, additional images or video clips can be received automaticallyand without user interaction. On receiving, operations of methods 1210can be performed again for these perceived additional images or videoclips. For example, consider a case where Bella selects to create ahighlight reel of herself. The final highlight reel can be generated butlater updated as Bella takes additional pictures of herself or receivesadditional pictures from friends. By so doing, reel generator 112 maycontinually update a highlight reel.

In the context of methods 1200, consider an example case where reelgenerator 112 receives an indication from a calendar application that auser and two friends have a shared calendar event to go to a party. Reelgenerator 112, at operation 1204, determines to highlight these personsor receives a selection from these friends to do so. At some point,photos and video (source media 120) is received from these three friendsthat, based on times at which the media was captured by the threefriends, can be determined to been taken during the party. Reelgenerator 112 can determine, or receive quality metric values, and basedon these three friends and the determined quality of the media, arrangeimages from this shared media into a reel preview at operation 1208.Assume that one of the friends approves the generated reel preview orpreviously selected to have a final highlight reel created withoutapproval, which is then shared with the three friends at operation 1216.In this example, the highlight reel is generated that highlights theparty and the friends with little or no time and effort required of thefriends.

In more detail, reel generator 112 may determine the images and videoclips to balance how many times each friend is shown, provide imageshaving all three friends in one photo (if possible), includehigher-quality images, and show different kinds of images (e.g., indifferent lighting, with different other people, video clips withhigher-quality audio, and so forth). Assume here that the total sourcemedia includes 15 minutes of video and 43 photos taken at the party andproduces a highlight reel that is roughly one minute long, includes 12of the 43 photos shown for two seconds each and 36 seconds of variousparts of the 15 minutes of video. This highlight reel is thus quicklyand easily enjoyed by the friends that went to (or while still at) theparty and with very little time and effort.

Example Methods for Weighting People or Contexts

As noted in methods 1200 above at operation 1204, the techniques maydetermine persons to highlight. In some cases persons are weighted insome manner. Consider methods 1300, illustrated in FIG. 13, whichincludes operations for weighting both persons and context as part ofhighlighting media.

Operations 1302, 1304, and 1306 are one manner in which operation 1204of methods 1200 can be performed, though operation 1204 is not limitedto operations of methods 1300.

At 1302, persons are determined to be in source media. This can bethrough various manners described herein, such as tagging, facialrecognition, association with an event or other person in the media, andso forth.

At 1304, a user interface enabling selection to weight the personsdetermined to be in the source media is presented. This user interfacecan enable selection in various manners, such as presenting thedetermined persons and enabling textual or graphical selection.

By way of example, consider FIG. 14, which illustrates weightinginterface 1402. In this example, selection to weight persons is enabledthrough slider bars 1404, each of the slider bars corresponding to aperson. Example images 1406 of each person are movable on the slider barto select the waiting for that person in the highlight reel. While shownin line drawing, these images 1406 for each person can be thumbnailsshowing each person's face pulled from source media (even the sourcemedia to be highlighted), avatars, or other identifiers.

Selection of multiple persons can be enabled through a single gesture aswell. An example single gesture is shown traced over weighting interface1402 at gesture trace 1408. Note that the current weightings of BellaBurke, Sarah Jones, Glendon Parker, and Mark Hansen are equal prior toselection. Responsive to receiving a single gesture, reel generator 112adjusts the weightings based on that single gesture, show atpost-selection weighting interface 1410. Here gesture trace 1408 is showagain to show the increase in the weighting of Bella Burke and GlendonParker, a large decrease in the weighting of Sarah Jones and a smallincrease in the weighting of Mark Hansen, all through this singlegesture selection. Slider bars 1404 and gesture selection as illustratedby gesture trace 1408 are but two of many ways in which the techniquesenable quick and easy selection to weight persons.

After persons and their weightings are received, the techniques mayproceed to other methods, such as methods 1200 or 500 to perform otherpreviously described operations. Thus, after weightings are received thetechniques may select a subset of media for highlighting, arrange in areel preview or highlight reel, present the preview or the highlightreel, and enable selection of alterations to the reel preview. Afterperforming other operations, the techniques may reweight persons atoperation 1308.

Assume, for example, that the techniques present a reel preview andenable selection to reweight the persons or to weight or reweightcontexts though an interface for altering the reel preview as notedelsewhere herein. At 1308, the persons can be reweighted in the variousmanners described or illustrated, such as in FIGS. 10 and 14. They mayalso be reweighted as illustrated in FIGS. 15 and 16.

FIG. 15 illustrates a size-based weighting interface 1502, whichpresents an image for each of the persons in the highlight reel orpreview, each of the images representing each person's face and having asize corresponding to the person's weighting in the highlight reel.Thus, current weightings (which correspond to weightings shown in FIG.14 at post-selection weighting interface 1410), are shown based on sizesof images for each of Bella, Sarah, Glendon, and Mark. Size-basedweighting interface 1502 enables selection to change weightings of thesepersons by altering their respective images. Thus, image 1504 for Sarahis shown with a gesture trace 1506 that completely removes Sarah to aweight of zero, shown with the gesture ending at a “Less” indicator.Image 1508 for Mark is shown with a gesture trace 1510 that increasesMark's weight but, based on an end point of the gesture trace (or amagnitude of the trace), indicates that Mark's weighting is to beincreased by a relatively small amount rather than a maximum amount. Theresult of these selections are shown at post-reweighting interface 1602of FIG. 16. Here Sarah is removed and Mark is increased to be about thesame weighting as Bella and Glendon. Through this process a user weightsand reweights her reel preview to result in a highlight reel thathighlights three persons only and about equally.

In each of these manners of selecting a weighting (whether person orcontext) the techniques may adjust a visual representation of anotherperson's weighting to compensate for the increase or decrease of anotherperson's weight. Thus, in the case of Sarah being removed, reelgenerator 112 may increase the size of the images for the other persons,as removing one person necessarily increases a weight of something else(e.g., another of the persons). In some cases this is not desired,however, and so one person may be altered without a visualrepresentation of how it affects the others being shown.

Returning to methods 1300, whether or not persons are reweighted atoperation 1308, in some optional cases methods 1300 proceed tooperations 1310, 1312, and 1314.

At 1310, weightings of contexts in the highlight reel or the reelpreview are determined. Contextual weightings can be determined as notedelsewhere herein.

At 1312, one or more of the weightings of the contexts are presented,and selection is enabled, in an interface. This can be performed asshown in FIG. 10, or in a manner similar to FIGS. 14, 15, and 16 but forcontexts rather than, or in addition to, persons. Thus a slider or sizehaving an image of a sun and trees can be used to enable selection toalter weightings for outdoor scenes and so forth.

At 1314, responsive to receiving selection to alter the one or moreweightings, the highlight reel or the reel preview is altered based onthe alteration to weighting the contexts. Continuing the currentexample, assume that Bella is presented with a high weighting of actionand outdoor scenes base on her wine tour album having mostly these sortsof images and video clips. She can select to alter theseweightings--assume here that when she watched the preview she didn'tlike the few indoor images and clips in the reel preview as they weren'twhat she was looking to highlight. She can simply reduce the weight ofthe indoor scenes, even to zero, or increase to maximum outdoor andaction scenes for a same result.

As noted methods 1300 may work in conjunction with other methods herein.For brevity these other operations, such as generating a highlight reeland sharing the reel, are not repeated here.

Example Device

FIG. 17 illustrates various components of an example device 1700including reel generator 112 as well as including or having access toother components of FIGS. 1 and 2. These components can implemented inhardware, firmware, and/or software and as described with reference toany of the previous FIGS. 1-16.

Example device 1700 can be implemented in a fixed or mobile device beingone or a combination of a media device, desktop computing device,television set-top box, video processing and/or rendering device,appliance device (e.g., a closed-and-sealed computing resource, such assome digital video recorders or global-positioning-satellite devices),gaming device, electronic device, vehicle, workstation, laptop computer,tablet computer, smartphone, video camera, camera, computing watch,computing ring, computing spectacles, and netbook.

Example device 1700 can be integrated with electronic circuitry, amicroprocessor, memory, input-output (I/O) logic control, communicationinterfaces and components, other hardware, firmware, and/or softwareneeded to run an entire device. Example device 1700 can also include anintegrated data bus (not shown) that couples the various components ofthe computing device for data communication between the components.

Example device 1700 includes various components such as an input-output(I/O) logic control 1702 (e.g., to include electronic circuitry) andmicroprocessor(s) 1704 (e.g., microcontroller or digital signalprocessor). Example device 1700 also includes a memory 1706, which canbe any type of random access memory (RAM), a low-latency nonvolatilememory (e.g., flash memory), read only memory (ROM), and/or othersuitable electronic data storage. Memory 1706 includes or has access toreel generator 112, highlight reel 116, quality metrics 118, sourcemedia 120, interface 122, associations 124, and relatedness 126. Reelgenerator 112 is capable of performing one more actions described forthe techniques. Other modules may also be included, such as aface-recognition engine (not shown), calendar application, eventplanning application, email application, and so forth.

Example device 1700 can also include various firmware and/or software,such as an operating system 1708, which, along with other components,can be computer-executable instructions maintained by memory 1706 andexecuted by microprocessor 1704. Example device 1700 can also includeother various communication interfaces and components, wireless LAN(WLAN) or wireless PAN (WPAN) components, other hardware, firmware,and/or software.

Other examples capabilities and functions of these entities aredescribed with reference to descriptions and figures above. Theseentities, either independently or in combination with other modules orentities, can be implemented as computer-executable instructionsmaintained by memory 1706 and executed by microprocessor 1704 toimplement various embodiments and/or features described herein.

Alternatively or additionally, any or all of these components can beimplemented as hardware, firmware, fixed logic circuitry, or anycombination thereof that is implemented in connection with the I/O logiccontrol 1702 and/or other signal processing and control circuits ofexample device 1700. Furthermore, some of these components may actseparate from device 1700, such as when remote (e.g., cloud-based)services perform one or more operations for reel generator 112. Forexample, photo and video (source, accessible, or in the highlight reel)are not required to all be in one location, some may be on a user'ssmartphone, some on a server, some downloaded to another device (e.g., alaptop or desktop). Further, some images may be taken by a device,indexed, and then stored remotely, such as to save memory resources onthe device.

Conclusion

Although highlighting media through weighting of people or contexts havebeen described in language specific to structural features and/ormethodological acts, the appended claims is not necessarily limited tothe specific features or acts described. Rather, the specific featuresand acts are disclosed as example forms of implementing techniques andapparatuses for highlighting media through weighting of people orcontexts.

1-20. (canceled)
 21. A method performed by a remote computing devicecomprising: receiving, by the remote computing device, a first set ofimages from a first computing device used by a first user; receiving, bythe remote computing device, a second set of images from a secondcomputing device used by a second user; determining, by the remotecomputing device, an association between the first set of images and thesecond set second images; creating, by the remote computing device inresponse to determining the association between the first set of imagesand the second set of images, a highlight reel, the highlight reelincluding one or more images from the first set of images and the secondset of images; and transmitting, to the first computing device used bythe first user, the highlight reel.
 22. The method of claim 21, whereindetermining the association between the first set of images and thesecond set of images is based on the remote computing device recognizingrespective faces of the first user and the second user within the firstset of images and the second set of images.
 23. The method of claim 21,wherein determining the association between the first set of images andthe second set of images is based, in part, on a tagging of the firstset of images that indicates: a face of the second user is present inthe first set of images; or the first set of images may be of interestto the second user.
 24. The method of claim 21, wherein determining theassociation between the first set of first images and the second set ofsecond images is based, in part, on a selection that tags the second setof set of images to indicate: a face of the first user is present in thesecond set of images; or the second set of images may be of interest tothe first user.
 25. The method as recited by claim 21, wherein the firstset of images includes at least one photo.
 26. The method as recited byclaim 21, wherein the first set of images includes at least one videoclip.
 27. The method as recited by claim 21, wherein the second set ofimages includes at least one photo.
 28. The method as recited by claim21, wherein the second set of images includes at least one video clip.29. The method of claim 21, further comprising: receiving, at thecomputing device from the first computing device, communicationsindicating permission to share the highlight reel; and transmitting, inresponse to receiving the communications indicating permission to sharethe highlight reel, the highlight reel to one or more other computingdevices.
 30. The method of claim 29, wherein transmitting the highlightreel to the one or more other computing devices includes transmittingthe highlight reel to the second computing device used by the seconduser.
 31. A non-transitory computer-readable storage media havinginstructions stored thereon that, responsive to execution by one or morecomputer processors of a remote computing device, perform operationsthat direct the remote computing device to: receive, by the remotecomputing device, a first set of images from a first computing deviceused by a first user; receive, by the remote computing device, a secondset of images from a second computing device used by a second user;determine, by the remote computing device, an association between thefirst set of images and the second set second images; create, by theremote computing device in response to the determination of theassociation between the first set of images and the second set ofimages, a highlight reel, the highlight reel including one or moreimages from the first set of images and the second set of images; andtransmit, to the first computing device used by the first user, thehighlight reel.
 32. The non-transitory computer-readable storage mediaof claim 31, wherein the determination of the association between thefirst set of images and the second set of images is based on the remotecomputing device recognizing respective faces of the first user and thesecond user within the first set of images and the second set of images.33. The non-transitory computer-readable storage media of claim 31,wherein the determination of the association between the first set ofimages and the second set of images is based, in part, on a selectionthat tags the first set of images to indicate that: a face of the seconduser is included in the first set of images; or the first set of imagesmay be of interest to the second user.
 34. The non-transitorycomputer-readable storage media of claim 31, wherein the determinationof the association between the first set of images and the second set ofimages is based, in part, on a selection that tags the second set ofimages to indicate that: a face of the first user is included in thesecond set of images; or the second set of images may be of interest tothe first user.
 35. A computing device comprising: an interface; animage-capture device; a communication component; a processor; and anon-transitory computer-readable storage media storing havinginstructions stored thereon that, responsive to execution by theprocessor, direct the computing device to: capture, using theimage-capture device, an image; receive, through the interface, a tagthat associates a person to the captured image; transmit, using thecommunication component and to a remote computing device, the capturedimage including the tag that associates the person to the capturedimage; receive, using the communication component and from the remotecomputing device, a highlight reel, the highlight reel including thecaptured image; present, through the interface, the highlight reel;receive, through the interface, a selection that indicates a permissionto share the highlight reel; and transmit, using the communicationcomponent and to the remote computing device, a communication thatindicates the permission to share the highlight reel.
 36. The computingdevice of claim 35, wherein the tag that associates the person to thecaptured image indicates a face of the person is within the captureimage.
 37. The computing device of claim 35, wherein the tag thatassociates the person to the captured image indicates that the capturedimage may be of interest to a person.
 38. The computing device of claim35, wherein the highlight reel further includes another image that isassociated to the image.
 39. The computing device of claim 38, whereinthe highlight reel includes audio.
 40. The computing device of claim 39,wherein the image and the another image each include a photo.